Zhejiang University, Hangzhou, Zhejiang Province 310058, China; Key Laboratory of Coastal Environment and Resources of Zhejiang Province, School of Engineering, Westlake University, Hangzhou, Zhejiang Province 310024, China.
Zhejiang University, Hangzhou, Zhejiang Province 310058, China.
Sci Total Environ. 2022 Oct 1;841:156624. doi: 10.1016/j.scitotenv.2022.156624. Epub 2022 Jun 10.
Extensive investigation of microplastic abundance in soil environment calls for rapid, accurate, efficient and harmonized quantification methods. Development of rapid quantification method requires made-to-measure soil samples with additions of standard polymers. Existing rapid quantification methods ignore the gap between standard polymers in laboratory and household microplastics in soil environment. Here, terahertz (0.6-1.67 thz) and NIR (950-1660 nm) spectroscopy were compared to explore a fast, accurate and potentially generalizable microplastic quantification method in soil. Soil sample was spiked with two standard polymers (polyvinyl chloride (PVC) and polystyrene (PS)) and their additive-containing household microplastics. Two standard sample sets and two household sample sets were prepared in concentrations ranging from 0.5 to 10%. Nine commonly used preprocessing methods and three machine learning algorithms were coupled to develop methods. Models were constructed by training sets from standard sample sets. When models transferred to household samples, prediction error (RMSE) of proposed terahertz method (Wdenosie_PLSR) only increased by 0.4% for PVC and 0.19% for PS, yet that of the NIR method increased by 1.49% and 1.16% respectively. The proposed terahertz method presented a detection limit around 1.12% and the NIR method showed a detection limit around 3.24%. Overall, our results suggest that compared with NIR method, the proposed terahertz method is not only more accurate but also demonstrate stronger generalizability to bridge the gaps between standard PVC/PS polymers and household PVC/PS microplastics. We also propose MMD heatmap for diagnosing spectral preprocessing methods to further improve method efficiency.
广泛调查土壤环境中微塑料的丰度需要快速、准确、高效和协调的定量方法。快速定量方法的开发需要使用具有标准聚合物添加物的定制土壤样品。现有的快速定量方法忽略了实验室标准聚合物与土壤环境中家庭微塑料之间的差距。在这里，太赫兹（0.6-1.67 thz）和近红外（950-1660nm）光谱被比较来探索一种快速、准确且具有潜在通用性的土壤中微塑料定量方法。土壤样品中加入了两种标准聚合物（聚氯乙烯（PVC）和聚苯乙烯（PS））及其含添加剂的家用微塑料。制备了两个标准样品集和两个家庭样品集，浓度范围从 0.5%到 10%。耦合了九种常用的预处理方法和三种机器学习算法来开发方法。通过标准样品集的训练集构建模型。当模型转移到家庭样本时，所提出的太赫兹方法（Wdenosie_PLSR）的预测误差（RMSE）仅对 PVC 增加了 0.4%，对 PS 增加了 0.19%，而近红外方法分别增加了 1.49%和 1.16%。所提出的太赫兹方法的检测限约为 1.12%，近红外方法的检测限约为 3.24%。总的来说，我们的结果表明，与近红外方法相比，所提出的太赫兹方法不仅更准确，而且具有更强的通用性，可以弥合标准 PVC/PS 聚合物与家庭 PVC/PS 微塑料之间的差距。我们还提出了 MMD 热图来诊断光谱预处理方法，以进一步提高方法效率。
